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In randomized trials with follow-up, outcomes may be undefined for individuals who die before the follow-up is complete. In such settings, Frangakis and Rubin [2002] proposed the “principal stratum effect” or “Survivor Average Causal Effect” (SACE), which is a fair treatment comparison in the subpopulation that would have survived(More)
The maximum likelihood estimation of hierarchical models for contingency tables is often carried out by the iterative proportional scaling (IPS) procedure. In this paper, we propose local computations of the IPS procedure by partitioning generators. The proposed implementation, called IPSP for short, first partitions generators into several non-overlapping(More)
In randomized trials with noncompliance, causal effects cannot be identified without strong assumptions. Therefore, several authors have considered bounds on the causal effects. Applying an idea of VanderWeele (), Chiba () gave bounds on the average causal effects in randomized trials with noncompliance using the information on the randomized assignment,(More)
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